Climate response in radial growth of Larix cajanderi and Pinus sylvestris in Central Yakutia

Climate change, characterized by increased temperature fluctuations and alterations in precipitation and soil moisture conditions, can significantly impact ecosystems that experience both moisture deficits and excesses. Even small changes in precipitation and air temperature can significantly affect tree growth. This paper examines the statistical parameters of the width of annual rings and the results of dendroclimatic analysis of larch (Larix cajanderi Mayr.) and pine (Pinus sylvestris L.) growing in the zone of continuous permafrost. The forest areas where larch and pine samples were collected are located near the village of Magan and the urban-type settlement of Nizhny Bestyakh in the central part of the Republic of Sakha (Yakutia). Woody plants are characterized by a longlife cycle, the annual rings of which are able to store information about their growth. This important resource allows obtaining valuable information about the climate and environmental changes in a given area. To understand how trees respond to climate change, Pearson correlation coefficients were calculated between the width of tree rings and average monthly air temperature, annual precipitation, and the SPEI aridity index using data from the Yakutsk weather station. To identify the response of different tree species to climate change over the past 30 years, each year was considered as a separate period. We assume that air temperature, which tends to increase, is one of the limiting factors that affects precipitation and dry periods. Due to the lack of moisture in the form of rain, tree species experience difficulties. They mainly receive moisture from the active layer of permafrost, which accumulates autumn precipitation of the previous year. Overall, we observe a negative response to the increase in air temperature in the surface layer of the atmosphere. On one hand, this suggests a decline in the radial growth of larch and pine; on the other hand, tree species are adapting to the changing climatic conditions in the central region of Yakutia.

1. Doloisio N., Vanderlinden J.-P. The perception of permafrost thaw in the Sakha Republic (Russia): Narratives, culture and risk in the face of climate change. Polar Science. 2020;26:100589. https://doi.org/10.1016/j.polar.2020.100589.

2. Ford J.D., Pearce T., Canosa I.V., et al. The rapidly changing Arctic and its societal implications. Wiley Interdisciplinary Reviews: Climate Change. 2021;12(6):e735. https://doi.org/10.1002/wcc.735.

3. Gustafson T. Klimat: Russia in the Age of Climate Change. Harvard University Press; 2021:336. https://doi.org/10.1080/09644016.2022.2123968.

4. Pearl J.K., Keck J.R., Tintor W., et al. New frontiers in tree-ring research. Holocene. 2020;30(6):923– 941. https://doi.org/10.1177/0959683620902230.

5. Lehmann M.M., Vitali V., Schuler P., et al. More than climate: Hydrogen isotope ratios in tree rings as novel plant physiological indicator for stress conditions. Dendrochronologia. 2021;65:125788. https://doi.org/10.1016/j.dendro.2020.125788.

6. Decuyper M., Chavez R.O., Cufar K., et al. Spatiotemporal assessment of beech growth in relation to climate extremes in Slovenia–An integrated approach using remote sensing and tree-ring data. Agricultural and Forest Meteorology. 2020;287:107925. https://doi.org/10.1016/j.agrfrormet.2020.107925.

7. Szejner P., Belmecheri S., Ehleringer J.R., et al. Recent increases in drought frequency cause observed multiyear drought legacies in the tree rings of semi-arid forests. Oecologia. 2020;192(1):241–259. https://doi.org/10.1007/s00442-019-04550-6.

8. Buntgen U., Allen K., Anchukaitis K.J., et al. The influence of decision-making in tree ring-based climate reconstructions. Nature communications. 2021;12(1):3411. https://doi.org/10.1038/s41467-021-23627-6.

9. Devi N.M., Kukarskih V.V., Galimova А.A., et al. Climate change evidence in tree growth and stand productivity at the upper treeline ecotone in the Polar Ural Mountains. Forest Ecosystems. 2020;7(1):1–16. https://doi.org/10.1186/s40663-020-0216-9.

10. Fedorov P.P., Desyatkin A.R. Relationship Between Temperature Regime of Permafrost Soils and Radial Growth of Larch in Central Yakutia. Advances in Current Natural Sciences.. 2016;(7):185–189. (In Russ.)

11. Kirdyanov A.V., Saurer M., Siegwolf R., et al. Long-term ecological consequences of forest fires in the continuous permafrost zone of Siberia. Environmental Research Letters. 2020;15(3):034061. https://doi.org/10.1088/1748-9326/ab7469.

12. Nikolaev A.N., Fedorov P.P. Influence of Climate Factors and Thermal Regime of Permafrost Soils in Central Yakutia on the Radial Growth of Larch and Pine. Forestry Studies. 2004;(6):3–13. (In Russ.)

13. Nikolaev A.N., Fedorov P.P., Desyatkin A.R. Influence of climate and soil hydrothermal regime on radial growth of Larix cajanderi and Pinus sylvestris in central Yakutia, Russia. Scandinavian Journal of Forest Research. 2009;24(3):217–226. https://doi.org/10.1080/02827580902971181.

14. Nikolaev A.N., Fedorov P.P., Desyatkin A.R. Effect of Hydrothermal Conditions of Permafrost Soil on Radial Growth of Larch and Pine in Central Yakutia. Contemporary Problems of Ecology. 2011;4(2):140–149. https://doi.org/10.1134/S1995425511020044.

15. Kolmogorov A.I., Kruse S., Nikolaev A.N., et al. Dendroclimatic studies of Larix cajanderi Mayr. in the Omoloy River Basin. Arctic and Subarctic Natural Resources. 2023;28(4):584–594. (In Russ.). https://doi.org/10.31242/2618-9712-2023-28-4-584-594.

16. Arzac A., Tychkov I.I., Rubtsov A., et al. Phenological shifts compensate warming-induced drought stress in southern Siberian Scots pines. European Journal of Forest Research. 2021;140:1487–1498. https://doi.org/10.1007/s10342-021-01412-w.

17. Arzac A., de Quijano D.D., Khotcinskaia K.I., et al. The buffering effect of the Lake Baikal on climate impact on Pinus sylvestris L. radial growth. Agricultural and Forest Meteorology. 2022;313:108764. https://doi.org/10.1016/j.agrformet.2021.108764.

18. Arzac A., Tabakova M.A., Khotcinskaia K., et al. Linking tree growth and intra-annual density fluctuations to climate in suppressed and dominant Pinus sylvestris L. trees in the forest-steppe of Southern Siberia. Dendrochronologia. 2021;67:125842. https://doi.org/10.1016/j.dendro.2021.125842.

19. Nikolaev A.N., Isaev A.P., Fedorov P.P. Radial Growth of Larch in Central Yakutia in Relation to Climate Change Over the Last 120 Years. Ecology. 2011;(4):243–250. (In Russ.)

20. Zhirnova D.F, Belokopytova L.V., Meko D.M., et al. Climate change and tree growth in the Khakass-Minusinsk Depression (South Siberia) impacted by large water reservoirs. Scientific reports. 2021;11(1):14266. https://doi.org/10.1038/s41598-021-93745-0.

21. Khotcinskaia K.I., Sergeeva O.V., Kirdyanov A.V., et al. Climatic Response of Radial Growth of Larix cajanderi in Northern and Central Yakutia. Moscow University Biological Sciences Bulletin, 2024;79(2): 94–100.

22. Arzac A., Popkova M., Anarbekova A., et al. Increasing radial and latewood growth rates of Larix cajanderi Mayr. and Pinus sylvestris L. in the continuous permafrost zone in Central Yakutia (Russia). Annals of Forest Science. 2019;76: 1–15.

23. Esper J., Frank D.C., Buntgen U., et al. Trends and uncertainties in Siberian indicators of 20th century warming. Global Change Biology. 2010;16:386–398. https://doi.org/10.1111/j.1365-2486.2009.01913.x.

24. Zhang X. Characteristics and response of radial growth of trees in Central Yakutia to climate change. Regional Environmental Issues. 2024;(3):16–21. (In Russ.). https://doi.org/10.24412/1728-323X-2024-3-16-21.

25. Rinn F. TSAP-Win: Time series analysis and presentation for dendrochronology and 409 related applications. User reference, Heidelberg. 2003. Available at: https://cir.nii.ac.jp/crid/1572543024876591616 (accessed: 10.11.2024).

26. Heeter K.J., Harley G.L., Maxwell J.T., et al. Summer temperature variability since 1730 CE across the low-to-mid latitudes of western North America from a tree ring blue intensity network. Quaternary Science Reviews. 2021;267:107064. https://doi.org/10.1016/j.quascirev.2021.107064.

27. Grissino-Mayer H.D. Evaluating crossdating accuracy: a manual and tutorial for the computer program COFECHA. Tree-ring Research. 2001;57(2):205–221.

28. R Core Team (2022) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. Available at: https://www.R-project.org (accessed 10.11.2024).

29. Bunn A.G. A dendrochronology program library in R (dplR). Dendrochronologia. 2008;26(2):115–124. https://doi.org/10.1016/j.dendro.2008.01.002.

30. Zang C., Blondi F. Treeclim: An R package for the numerical calibration of proxy-climate relationships. Ecography. 2015;38(4):431–436. https://doi.org/10.1111/ecog.01335.

31. Vicente-Serrano S.M., Begueria S., Lorez-Moreno J.I. A multi-scalar drought index sensitive to global warming: the Standardized Precipitation Evapotranspiration Index. Journal of Climate. 2010;23:1696–1718.

32. Zhang X.H., Nikolaev A.N., Kolmogorov A.I., et al. The Influence of Hydrothermal Moistening on the Radial Growth of Larch in Central Yakutia. Moscow University Biological Sciences Bulletin. 2024;79(2):101– 106. https://doi.org/10.3103/S0096392524600911.